Lidar Reflective Tomography of the Target Under Incomplete View State

Abstract

The lidar reflective tomography (LRT) system transmits a laser signal and obtains laser reflection projections of the target, which shows great potential for further long-distance noncooperative target detection. However, the received projections are normally in an incomplete view state. Hence, in this article, an improved algebraic reconstruction technique (ART) utilizing the sparse regularization model and nonlocal means (NLMs) algorithm is introduced and proposed for LRT reconstruction to restore incomplete signals or projections. By using the designed LRT outfield system, the comparative experiments are carried out to validate the effectiveness of the proposed method. By considering different investigation states, the improved NLM-ART sparse method shows great capability for LRT of noncooperative targets in long distance.